{"title":"粒子群算法在地震定位中的应用","authors":"Dong-xue Han, Gai-yun Wang","doi":"10.1109/WGEC.2009.48","DOIUrl":null,"url":null,"abstract":"The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Application of Particle Swarm Optimization to Seismic Location\",\"authors\":\"Dong-xue Han, Gai-yun Wang\",\"doi\":\"10.1109/WGEC.2009.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.\",\"PeriodicalId\":277950,\"journal\":{\"name\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WGEC.2009.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third International Conference on Genetic and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WGEC.2009.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Particle Swarm Optimization to Seismic Location
The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.